Integrating network and intrinsic changes in the GnRH neuron control of ovulation

 描述(由申请人提供)：生殖成功需要精确的排卵时间。当雌二醇从对垂体和下丘脑的负反馈作用转变为正反馈作用时，就会触发排卵，从而引发促性腺激素释放激素(GnRH)的分泌激增，从而导致黄体生成素(LH)的释放激增，从而触发排卵。我们对从负反馈到正反馈的神经生物学变化的理解是不完整的。高水平的雌二醇是必不可少的，在人类和啮齿动物中，黄体生成素高峰往往发生在一天中的特定时间段。然而，GnRH神经元不表达反馈所需的雌激素受体，因此雌激素敏感的传入可能将雌激素信息传递给GnRH神经元。同样，一天中的时间信息直接或间接地从视交叉上核(SCN)的哺乳动物中央时钟传递。我们的工作假设是，GnRH神经元通过整合突触输入和内在特性的多种变化，从负反馈切换到正反馈。为了验证这一假设，我们将在三个目标中使用三种不同的方法。 在Aim1中，我们将检验SCN神经调节剂血管活性肠肽直接作用于GnRH神经元以改变固有特性从而导致动作电位放电率增加的假设。在目标2中，我们假设转录和翻译的变化发生在从负反馈到正反馈的转变过程中。为了验证这一点，我们将使用分离的mRNA转录本结合到GFP标记的核糖体亚单位，这些亚单位在GnRH启动子的控制下使用cre重组酶靶向GnRH神经元。这将使我们能够在这个反馈转换过程中描述整个“转录组”。我们观察到的差异可能在改变调节开关的内在属性方面发挥作用。在目标3中，我们将开发一个GnRH神经元的数学模型，该模型结合了文献以及目标1和2中观察到的对固有属性和突触传递的所有个体变化。虽然电生理学实验仅限于一次操作一个或两个变量，但数学模型具有能够集成并同时操作所有变量的优势。通过反复调整电导，我们将能够预测哪种或哪些性质的组合复制了从负反馈到正反馈的切换。该模型将产生可检验的假设。我们的长期目标是促进对排卵神经控制所需信号的基本理解，以及该系统的扰动如何导致不孕不育。我们在这里开发的整合雌二醇和SCN信号的数学模型将帮助我们设计协议，以了解其他信号的整合，如代谢，到生殖功能。此外，这项研究将培训我在RNA分离和剖析电生理技术以及使用数学建模生成假说方面的能力。这种培训对于我成为一名独立的“湿”和“干”实验室内科科学家来说是必不可少的。

 DESCRIPTION (provided by applicant): Precise timing of ovulation is required for reproductive success. Ovulation is triggered when estradiol switches from negative feedback action on the pituitary and hypothalamus to positive feedback, initiating a surge of gonadotropin-releasing hormone (GnRH) secretion that causes a surge of luteinizing hormone (LH) release, which triggers ovulation. Our understanding of the neurobiological changes underlying the switch from negative to positive feedback is incomplete. High levels of estradiol are essential and, in both humans and rodents, the LH surge tends to occur at a specific time of day. GnRH neurons, however, do not express the estrogen receptor required for feedback, thus estradiol-sensitive afferents likely convey estradiol information to GnRH neurons. Likewise, time-of-day information is relayed directly or indirectly from the central mammalian clock in the suprachiasmatic nucleus (SCN). Our working hypothesis is that GnRH neurons switch from negative to positive feedback by integrating multiple changes to their synaptic inputs and intrinsic properties. To test this hypothesis, we will use three separate approaches in three aims. In Aim1, we will test the hypothesis that SCN neuromodulator vasoactive intestinal peptide acts directly on GnRH neurons to change intrinsic properties resulting in increased action potential firing rate. In Aim 2, we hypothesize that changes to transcription and translation occur during the transition from negative to positive feedback. To test this, we will use isolate mRNA transcripts bound to GFP-tagged ribosomal subunits that are targeted to GnRH neurons using cre recombinase under the control of the GnRH promoter. This will allow us to profile the entire "transcriptome" during this feedback transition. The differences we observe may have a role in modifying intrinsic properties that mediate the switch. In Aim 3, we will develop a mathematical model of a GnRH neuron that incorporates all the individual changes to intrinsic properties and synaptic transmission observed in the literature and in Aims 1 and 2. While electrophysiological experiments are limited to manipulating one or two variables at a time, mathematical models have the advantage of being able to integrate and simultaneously manipulate all variables. By iteratively adjusting conductances, we will be able to predict which combination or combinations of properties reproduce the switch from negative to positive feedback. This model will generate testable hypotheses. Our long-term goal is to advance the fundamental understanding of the signals required for neural control of ovulation, and how perturbations to this system lead to infertility. The mathematical models we develop here to integrate estradiol and SCN signals will help us to devise protocols to understand the integration of other signals, such as metabolism, into reproductive function. Furthermore, this research will train me in RNA isolation and profiling electrophysiological techniques and hypothesis generation using mathematical modeling. This training is essential for my evolution into an independent "wet" and "dry" lab physician scientist.